Worker Allocation Control for Changing Efficiency and Movement Cost
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Solution Overview
Problem
Existing methods for allocating workers across work sections in processes like relay-type picking struggle to accurately account for changes in work efficiency, leading to decreased efficiency due to movement costs and unpredictable workload distribution.
Innovation Solution
A work management device that acquires work evaluation indices based on historical data, estimates duration times, and determines worker allocation to maximize overall work efficiency by considering movement costs and changing workloads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If workers are reallocated to balance workload across work sections, then overall work efficiency is improved, but movement costs (time and resources) are incurred
Solution Approach 1:
The system calculates and stores movement costs in advance for all possible worker transitions between work sections. When workload balancing is needed, these pre-calculated costs are used to determine the optimal reallocation strategy, avoiding the need for real-time calculation and enabling faster decision-making while considering all movement implications.
Solution Approach 2:
The system continuously monitors workload distribution across work sections and automatically triggers reallocation when imbalances are detected. The feedback loop compares current workload states against optimal distributions, calculates the necessary worker movements, and implements adjustments while tracking the effectiveness of previous reallocations to improve future decisions.
2Productivity
If worker allocation is changed frequently to adapt to changing workloads, then work efficiency is maintained, but movement costs accumulate
Solution Approach 1:
The system dynamically adjusts worker allocations based on real-time workload changes while considering the cumulative movement costs. It evaluates whether the expected efficiency gain from reallocation outweighs the movement costs, and only triggers changes when beneficial. The system adapts to changing work patterns over time while learning from previous reallocation outcomes.
Solution Approach 2:
The system changes the allocation parameters (which worker goes to which work section) only when the workload imbalance exceeds a certain threshold or when the predicted efficiency improvement justifies the movement cost. This selective parameter change approach prevents unnecessary reallocations and accumulative movement costs while maintaining efficiency when needed.
3Productivity
If the number of workers in each work section is increased to handle peak workloads, then productivity is improved, but labor costs increase
Solution Approach 1:
The system merges the management of multiple work sections by dynamically allocating workers across section boundaries based on real-time workload demands. Instead of maintaining fixed staffing levels in each section, workers are pooled and redistributed as needed, allowing the system to handle peak workloads in any section using the total available workforce rather than requiring permanent additional staff in each location.
Data Source
AI summary
Provided is a work management device for arranging a worker in consideration of a change of work efficiency. In a work management device 10, an index acquisition unit 11 acquires, for each work section, a work evaluation index calculated based on work history performed by a worker. A duration time acquisition unit 12 acquires a duration time for which a work status of the worker is the work evaluation index. A cost acquisition unit 13 acquires a cost incurred when the worker moves between the work sections. A determination unit 14 acquires an estimated work amount performed by the worker until the duration time is elapsed. The determination unit 14 determines, based on the estimated work amount and cost, arrangement of the workers in the plurality of work sections in such a way as to increase work efficiency in a whole of a work range.